The present invention relates to providing smoothed digital images with reduced noise.
One type of noise found in digital camera images appears as low frequency, colored blobs in regions of low spatial frequency, e.g., a person""s face. These blobs, a type of chroma noise, produce a mottled appearance in an otherwise spatially flat region. These colored blobs are irregularly shaped and are typically 5 to 25, or more, pixels wide in a given direction.
There are numerous ways in the prior art for reducing chroma noise in digital images. Among these are numerous patents that describe chroma noise reduction methods using optical blur filters in digital cameras to avoid aliasing induced chroma noise in the first place. However, these blur filters generally address only high frequency chroma noise, and are generally ineffective against low frequency chroma noise.
Another very common approach to chroma noise reduction is to simply use standard grayscale image noise reduction techniques on each color channel of the image, in effect, treating each color channel as a separate grayscale image. By treating a full-color image as three, unrelated grayscale images, any interactions or correlations between the color channels are ignored. As discussed below, the inherent relationships between the color planes of a digital image can be used to perform more effective chroma noise cleaning, for example, by transforming the image into a different color space that permits for easier separation of image noise from genuine scene content.
Some approaches deal specifically with digital image processing methods for reducing or removing chroma noise artifacts. One class of digital camera patents discloses improvements to the color filter array (CFA) interpolation operation to reduce or eliminate high frequency chroma noise artifacts. Another class of patents teach using different pixel shapes (i.e., rectangles instead of squares) and arrangements (e.g., each row is offset by half a pixel width from the preceding row) with accompanying CFA interpolation operations to reduce or eliminate chroma noise artifacts. Again, these techniques address only high frequency chroma noise, and are generally ineffective against low frequency chroma noise.
There is the well known technique in the open literature of taking a digital image with chroma noise artifacts, converting the image to a luminancexe2x80x94 chrominance space, such as CIELAB, blurring the chrominance channels and then converting the image back to the original color space. This operation is a standard technique used to combat chroma noise. One liability with this approach is that there is no discrimination during the blurring step between chroma noise artifacts and genuine chroma scene detail. Consequently, sharp colored edges in the image begin to bleed color as the blurring become more aggressive. Usually, the color bleed has become unacceptable before most of the low frequency, colored blobs are removed from the image. Also, if any subsequent image processing is performed on the image, there is the possibility of amplifying the visibility of the color bleeding. A second liability of this approach is that a small, fixed blur kernel is almost required to try to contain the problem of color bleeding. However, to address low frequency chroma blobs, large blur kernels would be needed to achieve the desired noise cleaning.
It is an object of the present invention to provide a chroma noise reduction method that permits for the use of large blur kernels while not causing color bleeding at sharp colored edges.
It is another object of this invention to provide an improved chroma noise cleaned digital image using variable shaped pixel neighborhood region blur kernels.
It is another object of the present invention to provide low frequency chroma blobs that can be removed from a digital image by using variable shaped pixel neighborhood region blur kernels.
These objects are achieved with a method for removing noise on a pixel by pixel basis from pixels of a digital image comprising the steps of:
producing a map of features in the digital image;
storing an original value of the pixel of interest from the map of features;
using values of features from the map to determine a variable shape neighborhood region of cleaning pixels with respect to the original value of the pixel of interest;
using the neighborhood region of cleaning pixels and the value of the pixel of interest to change the original value of the pixel of interest in the digital image so that it has been noise cleaned; and
repeating the steps above for other pixels of interest.
The present invention overcomes the limitation of the xe2x80x9cchroma blur trickxe2x80x9d by first identifying all of the edges and boundaries in the image and then permitting each calculation neighborhood region to adaptively grow until it encounters an edge or boundary. Consequently, color bleed is avoided while still permitting the use of large area blurring operations to eliminate chroma noise artifacts.
Features of this invention include:
1) automated operation (no user intervention is required, although the user could be given access to some algorithm parameters to control the aggressiveness of image modification); and
2) locally adaptive, variable sized calculation neighborhood region (very low spatial frequency artifacts can be eliminated in flat regions without forcing the use of the same large calculation neighborhood region size in spatially busy areas).
A novel aspect of this invention is the use of a locally adaptive, variable sized calculation neighborhood region that keys off of an edge feature map to permit the maximum amount of chroma noise removal without significant degradation to genuine scene detail.